A framework for community curation of interspecies interactions literature

The quantity and complexity of data being generated and published in biology has increased substantially, but few methods exist for capturing knowledge about phenotypes derived from molecular interactions between diverse groups of species, in such a way that is amenable to data-driven biology and research. To improve access to this knowledge, we have constructed a framework for the curation of the scientific literature studying interspecies interactions, using data curated for the Pathogen–Host Interactions database (PHI-base) as a case study. The framework provides a curation tool, phenotype ontology, and controlled vocabularies to curate pathogen–host interaction data, at the level of the host, pathogen, strain, gene, and genotype. The concept of a multispecies genotype, the ‘metagenotype,’ is introduced to facilitate capturing changes in the disease-causing abilities of pathogens, and host resistance or susceptibility, observed by gene alterations. We report on this framework and describe PHI-Canto, a community curation tool for use by publication authors.


Introduction
Recent technological advancements across the biological sciences have resulted in an increasing volume of peer-reviewed publications reporting experimental data and conclusions. To increase the value of this highly fragmented knowledge, biocurators manually extract the data from publications and represent it in a standardized and interconnected way following the FAIR (Findable, Accessible, Interoperable, and Reusable) Data Principles (International Society for Biocuration, 2018;Wilkinson et al., 2016). Curated functional data is then made available in online databases, either organism-or clade-specific (e.g. model organism databases) or those supporting multiple kingdoms of life (e.g. PHI-base Urban et al., 2022), Alliance of Genomes Resources (Agapite et al., 2020), or UniProt (Bateman et al., 2021). Due to the complexity of the biology and the specificity of the curation requirements, manual biocuration is currently the most reliable way to capture information about function and phenotype in databases and knowledge bases . For pathogen-host interactions, the original publications do not provide details of specific strains, variants, and their associated genotypes and phenotypes, nor the relative impact on pathogenicity and virulence, in a standardized machine-readable format. The expert curator synergizes knowledge from different representations (text, graphs, images) into clearly defined machine-readable syntax. The development of curation tools with clear workflows supporting the use of biological ontologies and controlled vocabularies has standardized curation efforts, reduced ambiguity in annotation, and improved the maintenance of the curated corpus as biological knowledge evolves (International Society for Biocuration, 2018).
The pathogen-host interaction research communities are an example of a domain of the biological sciences exhibiting a literature deluge (Figure 1). PHI-base (phi-base.org) is an open-access FAIR biological database containing data on bacterial, fungal, and protist genes proven to affect (or not to affect) the outcome of pathogen-host interactions (Rodríguez-Iglesias et al., 2016;Urban et al., 2020;Urban et al., 2022). Since 2005, PHI-base has manually curated phenotype data associated with underlying genome-level changes from peer-reviewed pathogen-host interaction literature. Information is also provided on the target sites of some anti-infective chemistries (Urban et al., 2020). Knowledge related to pathogen-host interaction phenotypes is increasingly relevant, as infectious microbes continually threaten global food security, human health across the life course, farmed animal health and wellbeing, tree health, and ecosystem resilience (Brown et al., 2012;Fisher et al., 2018;Fisher et al., 2012;Fisher et al., 2022;Smith et al., 2019). Rising resistance to antimicrobial compounds, increased globalization, and climate change indicate that infectious microbes will present ever-greater economic and societal threats (Bebber et al., 2013;Chaloner et al., 2021;Cook et al., 2021). In eLife digest The increasingly vast amount of data being produced in research communities can be difficult to manage, making it challenging for both humans and computers to organise and connect information from different sources. Currently, software tools that allow authors to curate peer-reviewed life science publications are designed solely for single species, or closely related species that do not interact.
Although most research communities are striving to make their data FAIR (Findable, Accessible, Interoperable and Reusable), it is particularly difficult to curate detailed information based on interactions between two or more species (interspecies), such as pathogen-host interactions. As a result, there was a lack of tools to support multi-species interaction databases, leading to a reliance on labour-intensive curation methods.
To address this problem, Cuzick et al. used the Pathogen-Host Interactions database (PHI-base), which curates knowledge from the text, tables and figures published in over 200 journals, as a case study. A framework was developed that could capture the many observable traits (phenotype annotations) for interactions and link them directly to the combination of genotypes involved in those interactions across multiple scales -ranging from microscopic to macroscopic. This demonstrated that it was possible to build a framework of software tools to enable curation of interactions between species in more detail than had been done before. Cuzick et al. developed an online tool called PHI-Canto that allows any researcher to curate published pathogen-host interactions between almost any known species. An ontology -a collection of concepts and their relations -was created to describe the outcomes of pathogen-host interactions in a standardised way. Additionally, a new concept called the 'metagenotype' was developed which represents the combination of a pathogen and a host genotype and can be easily annotated with the phenotypes arising from each interaction.
The newly curated multi-species FAIR data on pathogen-host interactions will enable researchers in different disciplines to compare and contrast interactions across species and scales. Ultimately, this will assist the development of new approaches to reduce the impact of pathogens on humans, livestock, crops and ecosystems with the aim of decreasing disease while increasing food security and biodiversity. The framework is potentially adoptable by any research community investigating interactions between species and could be adapted to explore other harmful and beneficial interspecies interactions. Figure 1. Increase of molecular pathogen-host interaction publications and gene-phenotype information during the last 35 years curated in the Pathogen-Host Interactions database (PHI-base). Gray bars show the number of publications in the Web of Science Core Collection database retrieved with search terms '(fung* or yeast) and (gene or factor) and (pathogenicity or virulen* or avirulence gene*).' Black vertical bars show the number of articles retrieved from PubMed (searching on title and abstract). White and black triangles show the number of curated plant and animal pathogen genes, respectively. by the concept of the 'disease triangle' (Figure 2). All these interrelated factors must be recorded in order to sufficiently describe a pathogen-host interaction.
In this study, three key issues were addressed in order to develop the curation framework for interspecies interactions: first, to support the classification of genes as 'pathogen' or 'host,' and enable the variations of the same gene in different strains to be captured; second, formulating the concept of a 'metagenotype' to represent the interaction between specific strains of both a pathogen and a host within a multispecies genotype; and thirdly, developing supporting ontologies and controlled vocabularies, including the generic Pathogen-Host Interaction Phenotype Ontology (PHIPO), to annotate phenotypes connected to genotypes at the level of a single species (pathogen or host) and multiple species (pathogen-host interaction phenotypes). Leading on from these advances, we discuss how the overall curation framework described herein, the concept of annotating metagenotypes, and ongoing generic ontology development, is a suitable approach for adoption and use by a wide range of research communities in the life sciences focused on different types of interspecies interactions occurring within or across kingdoms in different environments and at multiple (micro to macro) scales. The disease triangle illustrates the requirement for the correct abiotic and biotic environmental conditions to ensure disease when an adapted pathogen encounters a suitable host. (b) A non-gene-for-gene genetic relationship where compatible interactions result in disease on all host genotypes (depicted as genotypes 1-4), but the extent of disease formation is influenced to a greater or lesser extent by the presence or absence of a single pathogen virulence gene product X. In host genotypes 1 and 3, the pathogen gene product X is the least required for disease formation. The size of each black oval in each of the eight genetic interactions indicates the severity of the disease phenotype observed, with a larger oval indicating greater severity. (c) A gene-for-gene genetic relationship. In this genetic system, considerable specificity is observed, which is based on the direct or indirect interaction of a pathogen avirulence (Avr) effector gene product with a host resistance (R) gene product to determine specific recognition (an incompatible interaction), which is typically observed in biotrophic interactions (Jones and Dangl, 2006). In one scenario, the product of the Avr effector gene binds to the product of the R gene (a receptor) to activate host resistance mechanisms. In another scenario, the product of the Avr effector gene binds to an essential host target which is guarded by the product of the R gene (a receptor). Once Avr effector binding is detected, host resistance mechanisms are activated. The absence of the Avr effector product or the absence of the R gene product leads to susceptibility (a compatible interaction). The small black dot indicates no disease formation, and the large black oval indicates full disease formation. (d) An inverse gene-for-gene genetic relationship. Again, considerable specificity is observed based on the interaction of a pathogen necrotrophic effector (NE) with a host susceptibility (S) target to determine specific recognition. The product of the pathogen NE gene binds to the product of the S gene (a receptor) to activate host susceptibility mechanisms.

Enabling multispecies curation with UniProtKB accessions
In any curation context, stable identifiers are required for annotated entities. The UniProt Knowledgebase (UniProtKB) (Bateman et al., 2021) is universally recognized, provides broad taxonomic protein coverage, and manually curates standard nomenclature across protein families. Protein sequences are both manually and computationally annotated in UniProtKB, providing a wealth of data on catalytic activities, protein structures, and protein-protein interactions, Gene Ontology (GO) annotations, and links to PHI-base phenotypes (Ashburner et al., 2000;Carbon et al., 2021;Urban et al., 2022). To improve interoperability with other resources, we used UniProtKB accession numbers for retrieving protein entities, gene names, and species information for display in PHI-Canto. PHI-Canto accesses the UniProtKB API to automatically retrieve the entities and their associated data.

Developing the metagenotype to capture interspecies interactions
To enable the annotation of interspecies interactions, we developed the concept of a 'metagenotype,' which represents the combination of a pathogen genotype and a host genotype (Figure 3). A   metagenotype is created after the individual genotypes from both species are created. Each metagenotype can be annotated with pathogen-host interaction phenotypes to capture changes in pathogenicity (caused by alterations to the pathogen) and changes in virulence (caused by alterations to the host and/or the pathogen). Pathogenicity is a property of the pathogen that describes the ability of the pathogen to cause an infectious disease in another organism. When a pathogenic organism causes disease, the severity of the disease that occurs is referred to as 'virulence' and this can also be dependent upon the host organism. Metagenotypes must always include at least one named pathogen gene with a genotype of interest, but need not include a host gene if none is referenced in a given experiment: instead, the wild-type host species and strain may be used for the host part of the metagenotype.

Annotation types and annotation extensions in PHI-Canto
In PHI-Canto, 'annotation' is the task of relating a specific piece of knowledge to a biological feature. Three types of biological features can be annotated in PHI-Canto: genes, genotypes, and metagenotypes. Genotypes can be further specified as pathogen genotypes or host genotypes. Each of these biological features has a corresponding set of annotation types. The relation between biological features, annotation types, and the values that can be used for annotation are shown in Table 1. To capture additional biologically relevant information associated with an annotation, curators use the concept of annotation extensions (which include Gene Ontology annotations described by Huntley et al., 2014) to extend the primary annotation. For Canto and PHI-Canto, the meaning of 'annotation extension' was broadened to capture additional properties related to the annotation, such as the metagenotype used as an experimental control. The aforementioned additional properties are simply referred to as 'annotation extensions (AEs)' in this study ( Metagenotypes can be annotated with terms from an ontology or controlled vocabulary following either the 'pathogen-host interaction phenotype,' 'gene-for-gene phenotype,' or 'disease name' annotation types (Table 1). Phenotype annotations on metagenotypes can be supported by AEs providing additional qualifying information required to fully interpret the experiment, such as the infected tissue of the host.
Phenotypes can also be curated for single-species experiments involving either the pathogen or host, following the 'single species phenotype' annotation workflow ( Table 1). Single species phenotype annotations have a selection of AEs available, including the protein assayed in the experiment and the severity of the observed phenotype (see an example from PMID:22314539 in Appendix 1).
PHI-Canto also supports the annotation of gene and gene product attributes to represent the evolved functional role of a gene product, described here as the 'gene annotation' workflow ( Table 1). The Gene Ontology is used for the annotation of a gene product's molecular functions, biological processes, and cellular components, while PSI-MOD is used for the annotation of protein modifications (Montecchi-Palazzi et al., 2008), and BioGRID experiment types are used to capture genetic and physical interactions (Oughtred et al., 2021). GO annotations are submitted to the EBI GO Annotation Database (GOA), from where they are propagated to the main GO knowledge base Huntley et al., 2015).

Trial curation of interspecies interaction publications
Ten publications covering a wide range of typical plant, human, and animal pathogen-host interactions were selected for trial curation in PHI-Canto before the tool was made available to publication authors and communities to add further publications ( Table 2). These publications included experiments with early-acting pathogen virulence proteins, the first host targets of pathogen effectors, and resistance to antifungal chemistries. These publications guided the development of the ontology terms and controlled vocabulary terms that were required for PHI-Canto, as well as the curation methods required for different experiments. Major curation problems and their solutions are summarized in Table 3, and example annotations are described below and in Appendix 1 and Appendix 2.

Curating an experiment with a metagenotype
A large proportion of the curation in PHI-Canto requires the use of metagenotypes: one of the simpler cases involves early-acting virulence proteins, where a genetically modified pathogen is inoculated onto a host (without a host gene being specified). A metagenotype is created to connect the genotypes of both species and is annotated with a phenotype term. These experiments are curated following the 'pathogen-host interaction phenotype' workflow, including any relevant AEs (Table 1). This two-step curation process is illustrated by PMID:29020037 curation ( Table 2, Appendix 1 and Appendix 2) where the GT2 gene is deleted from the fungal plant pathogen Zymoseptoria tritici and inoculated onto wheat plants; the observed phenotype 'absence of pathogen-associated host lesions'

Curating pathogen effector experiments
A pathogen effector is defined as an entity transferred between the pathogen and the host that is known or suspected to be responsible for either activating or suppressing a host process commonly involved in defense (Houterman et al., 2009;Jones and Dangl, 2006; Figure 2). To curate an effector experiment, a metagenotype is created and annotated with a phenotype term. To indicate that the pathogen gene functions as an effector, it is necessary to make a concurrent gene annotation (Table 1) with the GO biological process term 'effector-mediated modulation of host process' (GO:0140418) or an appropriate descendant term. This GO term (GO:0140418) and its descendant terms were created in collaboration with the Gene Ontology Consortium (GOC) and are used for pathogen effectors in PHI-base (version 5) (Supplementary file 3). Reported activities of pathogen effectors can also be curated with GO molecular function terms. An example of curation of a pathogen effector experiment is illustrated using PMID:31804478 ( Table 2 and Appendix 1) where the pathogen effector Pst_12806 from Puccinia striiformis suppresses pattern-triggered immunity in a tobacco leaf model. Here, the metagenotype is annotated with the phenotype 'decreased level of host defenseinduced callose deposition' (PHIPO:0001015) and the effector is annotated with 'effector-mediated suppression of host pattern-triggered immunity' (GO:0052034). A further experiment demonstrated that the pathogen effector protein was able to bind to the natural host (wheat) protein PetC and inhibit its enzyme activity, resulting in a GO molecular function annotation 'enzyme inhibitor activity' (GO:0004857) for Pst_12806, with PetC captured as the target protein (see Appendix 1).

Curating experiments with a gene-for-gene relationship
For a gene-for-gene pathogen-host interaction type, the 'gene-for-gene phenotype' metagenotype workflow is followed (a gene-for-gene interaction is when a known genetic interaction is conferred by a specific pathogen avirulence gene product and its cognate host resistance gene product) (Figure 2c and d, further described in the figure legend Flor, 1956;Jones and Dangl, 2006;Kanyuka et al., 2022). The metagenotypes and phenotype annotations are made in the same way as the standard 'pathogen-host interaction phenotype' workflow, but with different supporting data. A new AE was created to indicate the following three components of the interaction: (i) the compatibility of the interaction, (ii) the functional status of the pathogen gene, and (iii) the functional status of the host gene. An example of an annotation for a biotrophic pathogen gene-for-gene interaction has been illustrated   Table 2 and Appendix 1). Inverse gene-for-gene relationships occur with necrotrophic pathogens, where the pathogen necrotrophic effector interacts with a gene product from the corresponding host susceptibility locus and activates a host response that benefits the pathogen (a compatible interaction). If the necrotrophic effector cannot interact with the host target, then no disease occurs (an incompatible interaction) (Breen et al., 2016). An example of an inverse gene-forgene interaction using the appropriate AEs is illustrated with PMID:22241993 ( Table 2 and Appendix  1).
Curating an experiment with a single species genotype in the presence or absence of a chemical Single species genotypes (pathogen or host) can also be annotated with phenotypes following the 'single species phenotype' workflow ( Table 1). This is illustrated using PMID:22314539 in Table 2 (and Appendix 1) with an example of an in vitro pathogen chemistry phenotype, where a single nucleotide mutation in the Aspergillus flavus cyp51C gene confers 'resistance to voriconazole' (PHIPO:0000590), an antifungal agent.

Supporting curation of legacy information
PHI-Canto's curation workflows maintain support for nine high-level terms that describe phenotypic outcomes essential for taxonomically diverse interspecies comparisons, which were the primary annotation method used in previous versions of PHI-base (Urban et al., 2015) and which are displayed in the Ensembl Genomes browser . For example, the 'infective ability' AE can be used to annotate the following subset of high-level terms: 'loss of pathogenicity,' 'unaffected pathogenicity,' 'reduced virulence,' 'increased virulence,' and 'loss of mutualism' (formerly 'enhanced antagonism'). The mapping between the nine high-level terms and the PHI-Canto curation process is further described in Supplementary file 3. Table 3 shows a selection of the problems encountered during the development of PHI-Canto and the solutions we identified: for example, recording the delivery mechanism used within the pathogen-host interaction experiment. New experimental condition terms were developed with a prefix of 'delivery mechanism': for example, 'delivery mechanism: agrobacterium,' 'delivery mechanism: heterologous organism,' and 'delivery mechanism: pathogen inoculation.' Another issue encountered was how to record a physical interaction between two proteins from different species, especially for the curation of pathogen effectors and their discovered first host targets. This was resolved by adapting the existing Canto module for curating physical interactions to support two different species.

Development of the Pathogen-Host Interaction Phenotype Ontology and additional data lists
To support the annotation of phenotypes in PHI-Canto, PHIPO was developed. PHIPO is a speciesneutral phenotype ontology that describes a broad range of pathogen-host interaction phenotypes. Terms in PHIPO were developed following a pre-compositional approach, where the term names and semantics were composed from existing terms from other ontologies, in order to make the curation process easier. For example, the curator annotates 'resistance to penicillin' (PHIPO:0000692) instead of annotating 'increased resistance to chemical' (PHIPO:0000022) and 'penicillin' (CHEBI:17334) separately. Terms in PHIPO have logical definitions that follow design patterns from the uPheno ontology (Shefchek et al., 2020), and mapping PHIPO terms to the uPheno patterns is an ongoing effort. These logical definitions provide relations between phenotypes in PHIPO and terms in other ontologies, such as PATO, GO, and ChEBI. PHIPO is available in OWL and OBO formats from the OBO Foundry (Jackson et al., 2021). PHI-Canto uses additional controlled vocabularies derived from data in PHI-base. To enable PHI-Canto to distinguish between pathogen and host organisms, we extracted a list of >250 pathogen species and >200 host species from PHI-base (Supplementary file 4). A curated list of strain names and their synonyms for the species currently curated in PHI-base was also developed for use in PHI-Canto (Supplementary files 4 and 5). PHI-base uses 'strain' as a grouping term for natural pathogen isolates, host cultivars, and landraces, all of which are included in the curated list. The curation of pathogen strain designations was motivated by the NCBI Taxonomy's decision to discontinue the assignment of strain-level taxonomic identifiers (Federhen et al., 2014) and a lack of standardized nomenclature for natural isolates of non-model species. New strain designations can be requested by curators and are reviewed by an expert prior to inclusion to ensure that each describes a novel strain designation rather than a new synonym for an existing strain.
Annotations in PHI-Canto include experimental evidence, which is specified by a term from a subset of the Evidence & Conclusion Ontology (ECO) (Giglio et al., 2019). Experimental evidence codes specific to pathogen-host interaction experiments have been developed and submitted to ECO. Phenotype annotations also include experimental conditions that are relevant to the experiment being curated, which are sourced from the PHI-base Experimental Conditions Ontology (PHI-ECO).
PHI-Canto includes a 'disease name' annotation type ( Table 1) for annotating the name of the disease caused by an interaction between the pathogen and host specified in a wild-type metagenotype (this annotation type is described in the PHI-Canto user documentation and in Appendix 2). Diseases are specified by a controlled vocabulary of disease names (called PHIDO), which was derived from disease names curated in previous versions of PHI-base (Urban et al., 2022). PHIDO was developed as a placeholder to allow disease names to be annotated on a wide variety of pathogen interactions, including those on plant, human, animal, and invertebrate hosts, especially where such diseases were not described in any existing ontology.

Summary of the PHI-Canto curation process
The PHI-Canto curation process is outlined in Figure 4, Figure 4-figure supplement 1, the PHI-Canto user documentation, a detailed worked example provided in Appendix 2 and curation tutorials on the PHI-base YouTube channel (https://www.youtube.com/@PHI-base), under the playlist 'PHI-Canto tutorial videos.' Each curation session is associated with one publication (using its PubMed identifier). One or more curators can collaborate on curating the same publication. An instructional email is sent by PHI-Canto to curators when they begin a new curation session, and PHI-base provides further guidelines on what information is needed to curate a publication in PHI-Canto (Figure 4figure supplement 2) and how to identify UniProtKB accession numbers from reference proteomes (Figure 4-figure supplement 3).
The curator first adds genes from the publication, then creates alleles from genes, genotypes from alleles, and metagenotypes from pathogen and host genotypes. Pathogen genotypes and host genotypes are created on separate pages, that only include genes from the relevant pathogen or host. A genotype can consist of multiple alleles, therefore, a metagenotype can contain multiple alleles from both the pathogen and the host. A 'copy and edit' feature allows the creation of multiple similar annotations.
To make annotations, the curator selects a gene, genotype, or metagenotype to annotate, then selects a term from a controlled vocabulary, adds experimental evidence, experimental conditions, AEs (where available), and any additional comments. The curator can also specify a figure or table number from the original publication as part of the annotation. Curators can use a term suggestion feature to suggest new terms for any controlled vocabulary used by PHI-Canto, and experimental conditions can be entered as free text if no suitable condition is found in PHI-ECO. Subsequently, new condition suggestions are reviewed and approved by expert curators. The curation session can be saved and paused at various stages during the curation process. Once the curation process is complete, the curator submits the session for review by a nominated species expert.

Display and interoperability of data
The process of incorporating FAIR principles fully into the PHI-base curation process will promote interoperability between data resources . Figure 5 illustrates the internal and external resource dependencies for curation in PHI-Canto. URLs and descriptions of the use of each resource are provided in Figure 5-figure supplement 1. All data curated in PHI-Canto will be displayed in the new gene-centric version 5 of PHI-base, introduced in Urban et al., 2022. Additional detail on the data types displayed in PHI-base 5 is available in Table 4. Reciprocally, components of the interspecies curation framework (Figure 6a) will provide data to other resources (Figure 6b). For example, GO terms will be used in curation with PHI-Canto and these annotations will be made Figure 4. Pathogen-Host Interaction Community Annotation Tool (PHI-Canto) curation workflow diagram. This diagram shows the curation workflow from the start of a curation session to its submission. The PubMed ID of the publication to be curated is entered and the title is automatically retrieved. The curator enters their name, email address, and ORCID iD. On the species and genes page, the experimental pathogen and host genes are entered using UniProtKB accession numbers, and for experiments where a mutant pathogen genotype is assayed on a wild-type host with no specified genes,

Figure 4 continued on next page
there is the option to select the host species from an autocomplete menu. Information on the specific experimental strains used for each species is entered. After entering this initial information, the curator follows one of three distinct workflows depending on the biological feature the user wants to annotate (metagenotype, genotype, or gene annotation type). Except for genes, biological features are created by composing less complex features: genotypes from alleles (generated in the pathogen or host genotype management pages), and metagenotypes from genotypes (generated in the metagenotype management page). Biological features are annotated with terms from a controlled vocabulary (usually an ontology), plus additional information that varies based on the annotation type. The curator has the option to generate further annotations after creating one, but this iterative process is not represented in the diagram for the sake of brevity. After all annotations have been made, the session is submitted into the Pathogen-Host Interactions database (PHI-base) version 5. * Note that the 'Ontology annotation' group covers multiple annotation types, all of which annotate biological features with terms from an ontology or controlled vocabulary. These annotation types are described in Table 1.
The online version of this article includes the following figure supplement(s) for figure 4:    Of the databases shown, the Pathogen-Host Interactions database (PHI-base) provides data (experimental conditions, disease names, and species strain names) used to create terms in the PHI-base controlled vocabularies; the UniProt Knowledgebase (UniProtKB) provides accession numbers for proteins that PHI-Canto uses to identify genes; and the NCBI Taxonomy database is used to generate a mapping file relating taxonomic identifiers lower than species rank to their nearest taxonomic identifiers at species rank. The OBO ontologies group contains ontologies in the OBO format that PHI-Canto uses for its annotation types. The parenthesized text after the ontology name indicates the term prefix for the ontology.
The online version of this article includes the following figure supplement(s) for figure 5: available in the GO knowledge base via submission to the GOA Database Huntley et al., 2015). PHI-base is a member of ELIXIR, an organization that aims to unite leading life science resources and is a major proponent of FAIR data (Durinx et al., 2016).

Discussion
Scalable and accurate curation of data within the scientific literature is of paramount importance due to the increasing quantity of publications and the complexity of experiments within each publication. PHI-base is an example of a freely available, manually curated database, which has been curating literature using professional curators since 2005 (Winnenburg et al., 2006).
Here, we have described the development of PHI-Canto to allow the curation of the interspecies pathogen-host interaction literature by professional curators and publication authors. This curated data is then made available on the new gene-centric version 5 of PHI-base, where all information (i.e. Figure 6. The interspecies curation framework and the interoperability of the Pathogen-Host Interaction Community Annotation Tool (PHI-Canto). (a) The interspecies curation framework consists of three main components. First, a curation tool called PHI-Canto, second, a new species-neutral phenotype ontology called PHIPO (the Pathogen-Host Interaction Phenotype Ontology), and thirdly, a selection of additional controlled vocabularies for disease names (PHIDO), experimental conditions (PHI-ECO), pathogen and host species, and natural strains associated with each species. The two-way arrows indicate that terms from the ontology and controlled vocabularies are used in curation with PHI-Canto, and that new terms required for curation may be suggested for inclusion within the ontology and controlled vocabularies. (b) The PHI-Canto and PHIPO content curation framework (gray box) uses persistent identifiers and cross-referenced information from UniProt, Ensembl Genomes, and the Gene Ontology. PHIPO is made available at the OBO Foundry. Newly minted wild-type gene annotations are suggested for inclusion into the Gene Ontology via the EBI Gene Ontology Annotation database. Data curated in PHI-Canto, following expert review, is then shared with ELIXIR data resources such as UniProtKB, Ensembl Genomes, FungiDB, and KnetMiner, and provided on request to other databases (FgMutantDB, GloBI). Researchers can look up curated information via the Pathogen-Host Interactions database (PHI-base) web interface or can download the whole dataset from PHI-base for inclusion in their bioinformatics pipelines. Authors can submit data to PHI-base by curating their publications into PHI-Canto. The origin of data is indicated by directional arrows. new and existing) on a single gene from several publications is presented on a single page, with links to external resources providing information on interacting genes, proteins, and other entities.
Several adaptations to the original single-species community annotation tool, Canto (Rutherford et al., 2014), were required to convert this tool for interspecies use. Notably, the need to annotate an interaction involving two different organisms necessitated the development of a novel concept, the 'metagenotype' (Figure 3), in order to record a combined experimental genotype involving both a pathogen and a host. This is, to our knowledge, the first example of such an approach to interspecies interaction curation.
Curation of pathogen-host interactions in PHI-Canto also necessitated the development of a new phenotype ontology (PHIPO) to annotate pathogen-host interaction phenotypes in sufficient detail across the broad range of host species that were curated in PHI-base (n=234 in version 4.14 of PHIbase). The functional annotation of genes involved in interspecies interactions is a complex and challenging task, requiring ongoing modifications to the Gene Ontology and occasional major refactoring to deprecate legacy terms . PHIPO development and maintenance will also be an ongoing task, with both authors and professional curators requesting new terms and edits to existing terms and the ontology structure. Maintenance will be made more sustainable by the incorporation of logical definitions that are aligned across phenotype ontologies in collaboration with the uPheno project (Shefchek et al., 2020).
To improve the efficiency of the curation process, we are suggesting that authors follow an author checklist during manuscript preparation (Appendix 3). This will improve the presentation of key information (e.g. species names, gene identifiers, etc.) in published manuscripts, thus enabling more efficient and comprehensive curation that is human-and machine-readable. The annotation procedures described here using PHI-Canto can be used to extract data buried in small-scale publications and increase the accessibility of the curated article to a wider range of potential users, for example, computational biologists, thereby improving the FAIR status of the data. The current data in PHIbase has been obtained from >200 journals (Figure 7) and, therefore, represents highly fragmented knowledge which is exceptionally difficult to use by professionals in other disciplines. The feasibility of scalable community curation with Canto is evidenced by PomBase (Lock et al., 2020), where Canto S. pombe annotations from over 1000 publications are provided by publication authors, with the data made available within 24 hr of review (https://curation.pombase.org/pombe/stats/annotation).
With regard to our focus on manual curation, we recognize that great progress has been made with machine learning (ML) approaches in recent times. However, Wood et al., 2022 note that the data being curated from publications are 'categorical, highly complex, and with hundreds of thousands of heterogeneous classes, often not explicitly labeled.' There are no published examples of ML approaches outperforming an expert curator in accuracy, which is paramount in the medical field. However, curation by experts could provide a highly reliable corpus that could be used for training ML systems. Our aspiration is that ML and expert curators can collaborate in a virtuous cycle whereby expert curators continually review and refine the ML models, while the manual work of finding publications and entity recognition is handled by the ML system.
Our future intentions are twofold: first, a graph-based representation of the data will be enabled by integration with knowledge network generation tools, such as Knetminer (Hassani-Pak et al., 2021), where subgraphs of the knowledge graph could be embedded into each gene-centric page on the PHI-base 5 website. Second, within PHI-Canto, we intend to address the issues associated with maximizing the inherent value of the natural sequence variation between species strains, and the associated altered phenotypic outcomes observed at multiple scales, in different types of interactions and/or environments. PHI-base already contains information on numerous species with multiple experimental strains, and natural sequence variation between strains can result in alterations at the genome level that affect the subsequently observed phenotypes. Strain-specific sequence variation is not captured in the reference proteomes stored by UniProt, even though accession numbers from these proteomes are often used in PHI-Canto. Currently, when a curator enters a gene with a taxonomic identifier below the species rank, PHI-Canto maps the identifier to the corresponding identifier at the species rank (thus removing any strain details from the organism name), and the curator specifies a strain to differentiate gene variants in naturally occurring strains. However, this does not change the taxonomic identifier linked to the UniProtKB accession number (nor its sequence), so the potential for inaccuracy remains. To mitigate this, the future plan is to record the strain-specific sequence of the gene using an accession number from a database from the International Nucleotide Sequence Database Collaboration (Arita et al., 2021).
The release of PHI-Canto to the community will occur gradually through various routes. Community curation will be promoted by working with journals to capture the publication data at the source, at the point of manuscript acceptance. We will also target specific research communities (e.g. those working on a particular pathogen and/or research topic) by inviting authors to curate their own publications. Authors may contact us directly to request support while curating their publications in PHI-Canto.
PHI-Canto, PHI-base, and PHIPO were devised and built over the past seven years to serve the research needs of a specific international research community interested in exploring the wide diversity of common and species-specific mechanisms underlying pathogen attack and host defense in plants, animals, humans, and other host organisms caused by fungi, protists and bacteria. However, it should be noted that the underlying developments to Canto's data model -especially the concept of annotating metagenotypes -could be of use to communities focused on different types of interspecies interactions. Possible future uses of the PHI-Canto schema could include insect-plant interactions (both beneficial and detrimental), endosymbiotic relationships such as mycorrhiza-plant rhizosphere interactions, nodulating bacteria-plant rhizosphere interactions, fungi-fungi interactions, plant-plant interactions or bacteria-insect interactions, and non-pathogenic relationships in natural environments such as bulk soil, rhizosphere, phyllosphere, air, freshwater, estuarine water or seawater, and humananimal, animal-bird, human-insect, animal-insect, bird-insect interactions in various anatomical locations (e.g. gut, lung, and skin). The schema could also be extended to situations where phenotype-genotype relations have been established for predator-prey relationships or where there is competition in herbivore-herbivore, predator-predator or prey-prey relationships in the air, on land, or in the water. Finally, the schema could be used to explore strain-to-strain interactions within a species when different biological properties have been noted. Customizing Canto to use other ontologies and controlled vocabularies is as simple as editing a configuration file, as shown in Source code 1.

Methods
Changes to the Canto data model and configuration PHI-Canto stores its data in a series of relational databases using the SQLite database engine. A primary database stores data shared across all curation sessions, and each curation session also has its own database to store data related to a single publication (such as genes, genotypes, metagenotypes, etc.). PHI-Canto can export its data as a JSON file or in more specialized formats, for example, the GO Annotation File (GAF) format.
To implement PHI-Canto several new entities were added to the Canto data model in order to support pathogen-host curation, as well as new configuration options (the new entities are illustrated in Figure 3-figure supplement 1). These entities were 'strain,' 'metagenotype,' and 'metagenotype annotation.' The complete data model for PHI-Canto is illustrated in Figure 3-figure supplements 2 and 3.

Pathogen and host roles
Genotype entities in PHI-Canto's data model were extended with an attribute indicating their status as a pathogen genotype or a host genotype. Genotypes inherit their status (as pathogen or host) from the organism, which in turn is classified as a pathogen or host based on a configuration file that contains the NCBI Taxonomy ID (taxid) (Schoch et al., 2020) of each host species in PHI-base. Only host taxids need to be specified since PHI-Canto defaults to classifying a species as a pathogen if its taxid is not found in the configuration file.
PHI-Canto also loads lists of pathogen and host species that specify the scientific name, taxid, and common name (if any) of each species. These species lists are used to specify which host species can be added as a component of the metagenotype in the absence of a specific studied gene, and to override the scientific name provided by UniProtKB in favor of the name used by a scientific community studying the species (for example, to control whether the anamorph or teleomorph name of a fungal species is displayed in PHI-Canto's user interface).

Metagenotype implementation
Metagenotypes were implemented by adding a 'metagenotype' entity to PHI-Canto's data model. The metagenotype is the composition of two genotype entities. We also changed the data model to allow annotations to be related to metagenotypes (previously, only genes and genotypes could be related to annotations).

Strain implementation
Support for strain curation was implemented by adding a 'strain' entity to PHI-Canto's data model. Strains are related to an organism entity and its related genotype entities. In the user interface, PHI-Canto uses the taxid of the organism to filter an autocomplete system, such that only the strains of the specified organism are suggested. The autocomplete system can also use synonyms in the strain list to suggest a strain based on its synonymous names. Unknown strains are represented by a preset value of 'Unknown strain.' Ontologies PHIPO was developed using the Protégé ontology editor (Musen and Team, 2015). PHIPO uses OBO namespaces to allow PHI-Canto to filter the terms in the ontology by annotation type, ensuring that genotypes are annotated with single-species phenotypes and metagenotypes with pathogen-host interaction phenotypes.
PHI-ECO was also developed using Protégé, starting from a list of experimental conditions originally developed by PomBase. PHIDO was initially derived from a list of diseases already curated in PHI-base and is now maintained as a flat file that is converted into an OBO file using ROBOT (Jackson et al., 2019).

Code availability
PHI-Canto's source code is available on GitHub, at https://github.com/PHI-base/canto, (copy archived at swh:1:rev:dd310334974d9471c1916c0ac080550bfd153707). PHI-Canto is freely licensed under the GNU General Public License version 3, with no restrictions on copying, distributing, or modifying the code, for commercial use or otherwise, provided any derivative works are licensed under the same terms. PHI-base provides an online demo version of PHI-Canto at https://demo-canto.phi-base.org/ which can be used for evaluating the tool. The demo version and the main version of PHI-Canto will remain freely available online.
The source code for PHI-Canto's user documentation is available on GitHub, at https://github.com/ PHI-base/canto-docs, (copy archived at swh:1:rev:a134c04d8fb59769678456fb41d02fd169be7b06). The user documentation is licensed under the MIT license. The published format of the user documentation is available online at https://canto.phi-base.org/docs/index.
• MDAR checklist • Source code 1. Main configuration file for the Pathogen-Host Interaction Community Annotation Tool (PHI-Canto). This is the main configuration file for PHI-Canto. Much of the configuration is inherited from Canto, the original curation application from which PHI-Canto is derived. Lines containing custom configuration for PHI-Canto have been indicated with comments Data availability Datasets generated for use within the curation framework are available as GitHub links in the manuscript section 'Data availability'. Code is available as GitHub links in the manuscript section 'Code availability'. PHI-Canto curated data is available here https://doi.org/10.5281/zenodo.7428788.
The following dataset was generated: Appendix 1

How to use annotation extensions
This file provides information on Annotation Extensions (AE) and how to use them in PHI-Canto to curate a standard selection of experiments ( Table 2). The first section provides four examples of using AEs for curating metagenotypes with pathogen-host interaction phenotypes. The second section provides examples of curating metagenotypes using the gene-for-gene phenotype workflow, including using the AEs for gene-for-gene interactions and inverse gene-for-gene interactions. The third section of this file illustrates three examples of using AEs for curating single-species phenotypes. Further information on how to use PHI-Canto to make annotations can be found in PHI-Canto's user documentation, available at https://canto.phi-base.org/docs/index. Contents: SECTION 1: Annotation Extensions for curating pathogen-host interaction phenotypes on metagenotypes • Section 1A: If you have a metagenotype phenotype recording 'unaffected pathogenicity' (corresponds to footnote ‡ in Table 2) • Section 1B: If you have a metagenotype phenotype recording 'altered pathogenicity or virulence' (corresponds to footnote § in Table 2) • Section 1C: If you have a metagenotype phenotype recording 'mutualism' (corresponds to footnote ** in Table 2) • Section 1D: If you have a metagenotype phenotype recording 'a pathogen effector' (corresponds to footnote † † in Table 2) SECTION 2: Annotation Extensions for curating gene-for-gene phenotypes on metagenotypes • Section 2A: If you have a metagenotype phenotype recording 'a gene-for-gene interaction' (corresponds to footnote ‡ ‡ in Table 2) • Section 2B: If you have a metagenotype phenotype recording 'an inverse gene-for-gene interaction' (corresponds to footnote ¶ ¶ in Table 2) SECTION 3: Annotation Extensions for curating single species phenotypes (pathogen phenotypes or host phenotypes) • Section 3A: Example of an in vitro pathogen phenotype (corresponds to footnote ¶ in Table 2) • Section 3B: Example of an in vitro pathogen chemistry phenotype (corresponds to footnote *** in Table 2) • Section 3C: Example of an in vivo host phenotype (corresponds to footnote § § in Table 2) Section 1: Annotation Extensions for curating pathogen-host interaction phenotypes on metagenotypes When creating and annotating metagenotypes, it is advisable to also create and annotate a wildtype control metagenotype where possible. This enables a better understanding of annotations made to altered metagenotypes. (Note: It is also possible to use several of the AEs in the table documenting single species phenotype AEs, e.g. penetrance and affected protein).
Section 1 A: If you have a metagenotype phenotype recording 'unaffected pathogenicity' (corresponds to footnote ‡ in Table 2 Example publication: The RhlR quorum-sensing receptor controls Pseudomonas aeruginosa pathogenesis and biofilm development independently of its canonical homoserine lactone autoinducer (PMID:28715477).

Specifying strains
Appendix 2-figure 7. The curator must enter the strains for each organism studied in the publication or must specify when the strain was not known (or not specified in the publication). The Pathogen-Host Interaction Community Annotation Tool (PHI-Canto) provides a pre-populated list of strains for many species that the curator can select from, though they also have the option to specify a strain not in the list as free text. In this publication, the pathogen strains are PH-1 for F. graminearum and IPO323 for Z. tritici. Two cultivars of T. aestivum were used: cv. Bobwhite and cv. Riband.

Creating alleles and genotypes
Appendix 2-figure 8. In order to show that deleting GT2 in the pathogen causes a loss of pathogenicity, the curator must annotate the interaction between the mutant pathogen and its host with a phenotype, meaning the interaction must be added to the curation session. In the Pathogen-Host Interaction Community Annotation Tool Appendix 2-figure 8 continued on next page Creating metagenotypes for pathogen-host interactions Appendix 2-figure 17. Metagenotypes are created using the Metagenotype management page, where genotypes previously added to the curation session can be combined into a metagenotype. The curator can reach this page from the Curation Summary page, or from either the pathogen, or host genotype management page.
Appendix 2-figure 18. The curator starts by selecting a pathogen species from a drop-down menu.
Appendix 2- figure 19. Then the curator selects a genotype from the table of pathogen genotypes.

Phenotype and evidence
Appendix 2-figure 27. The first step is to select a term from a controlled vocabulary that describes the phenotype of the interaction. The Pathogen-Host Interaction Community Annotation Tool (PHI-Canto) uses terms from the Pathogen-Host Interaction Phenotype Ontology (PHIPO) for this purpose. The primary observed phenotype, in this case, is the absence of pathogen-associated host lesions (PHIPO:0000481).
Appendix 2-figure 28. Upon selecting the term, the curator is shown a description of the term and its synonyms to help confirm that their chosen term is appropriate.